Anthropometric measurements are essential in various fields, such as sports, the automotive industry, clothing, health care, biomechanics, ergonomics, and gait analysis. However, the data collection process for these measurements is costly and time-consuming, and the data collected are not always precise and accurate. In this paper, some of the most widely reported machine vision systems (MVSs) are evaluated to determine the anthropometric length of body segments (BSs) used in gait analysis. The aim is to evaluate the performance of the MVSs and identify the most appropriate vision approach, in terms of accuracy, cost, speed, and computing performance. For this purpose, five BSs of the lower limb were selected and measured using both the MVS and the conventional manual anthropometric measurement (MAM) techniques. The results show that the MVSs represent an excellent alternative to measure the anthropometric parameters corresponding to the BSs, with some advantages in terms of sampling process time, precision, and equipment requirements.
